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  • richardmitnick 9:19 pm on January 12, 2018 Permalink | Reply
    Tags: , Bulk Fermi arc, MIT, Non-Hermitian systems, Photonic crystals, , Topological effects in open systems   

    From MIT: “New exotic phenomena seen in photonic crystals” 

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    January 11, 2018
    David L. Chandler

    1
    A drawing illustrates the unusual topological landscape around a pair of features known as exceptional points (red dots), showing the emergence of a Fermi arc (pink line at center), and exotic polarization contours that form a Mobius-strip-like texture (top and bottom strips). Courtesy of the researchers.

    Researchers observe, for the first time, topological effects unique to an “open” system.

    Topological effects, such as those found in crystals whose surfaces conduct electricity while their bulk does not, have been an exciting topic of physics research in recent years and were the subject of the 2016 Nobel Prize in physics. Now, a team of researchers at MIT and elsewhere has found novel topological phenomena in a different class of systems — open systems, where energy or material can enter or be emitted, as opposed to closed systems with no such exchange with the outside.

    This could open up some new realms of basic physics research, the team says, and might ultimately lead to new kinds of lasers and other technologies.

    The results are being reported this week in the journal Science, in a paper by recent MIT graduate Hengyun “Harry” Zhou, MIT visiting scholar Chao Peng (a professor at Peking University), MIT graduate student Yoseob Yoon, recent MIT graduates Bo Zhen and Chia Wei Hsu, MIT Professor Marin Soljačić, the Francis Wright Davis Professor of Physics John Joannopoulos, the Haslam and Dewey Professor of Chemistry Keith Nelson, and the Lawrence C. and Sarah W. Biedenharn Career Development Assistant Professor Liang Fu.

    In most research in the field of topological physical effects, Soljačić says, so-called “open” systems — in physics terms, these are known as non-Hermitian systems — were not studied much in experimental work. The complexities involved in measuring or analyzing phenomena in which energy or matter can be added or lost through radiation generally make these systems more difficult to study and analyze in a controlled fashion.

    But in this work, the team used a method that made these open systems accessible, and “we found interesting topological properties in these non-Hermitian systems,” Zhou says. In particular, they found two specific kinds of effects that are distinctive topological signatures of non-Hermitian systems. One of these is a kind of band feature they refer to as a bulk Fermi arc, and the other is an unusual kind of changing polarization, or orientation of light waves, emitted by the photonic crystal used for the study.

    Photonic crystals are materials in which billions of very precisely shaped and oriented tiny holes are made, causing light to interact in unusual ways with the material. Such crystals have been actively studied for the exotic interactions they induce between light and matter, which hold the potential for new kinds of light-based computing systems or light-emitting devices. But while much of this research has been done using closed, Hermitian systems, most of the potential real-world applications involve open systems, so the new observations made by this team could open up whole new areas of research, the researchers say.

    Fermi arcs, one of the unique phenomena the team found, defy the common intuition that energy contours are necessarily closed curves. They have been observed before in closed systems, but in those systems they always form on the two-dimensional surfaces of a three-dimensional system. In the new work, for the first time, the researchers found a Fermi arc that resides in the bulk of a system. This bulk Fermi arc connects two points in the emission directions, which are known as exceptional points — another characteristic of open topological systems.

    The other phenomenon they observed consists of a field of light in which the polarization changes according to the emission direction, gradually forming a half-twist as one follows the direction along a loop and returns back to the starting point. “As you go around this crystal, the polarization of the light actually flips,” Zhou says.

    This half-twist is analogous to a Möbius strip, he explains, in which a strip of paper is twisted a half-turn before connecting it to its other end, creating a band that has only one side. This Möbius-like twist in light polarization, Zhen says, could in theory lead to new ways of increasing the amount of data that could be sent through fiber-optic links.

    The new work is “mostly of scientific interest, rather than technological,” Soljačić says. Zhen adds that “now we have this very interesting technique to probe the properties of non-Hermitian systems.” But there is also a possibility that the work may ultimately lead to new devices, including new kinds of lasers or light-emitting devices, they say.

    The new findings were made possible by earlier research [Science Advances] by many of the same team members, in which they found a way to use light scattered from a photonic crystal to produce direct images that reveal the energy contours of the material, rather than having to calculate those contours indirectly.

    “We had a hunch” that such half-twist behavior was possible and could be “quite interesting,” Soljačić says, but actually finding it required “quite a bit of searching to figure out, how do we make it happen?”

    “Perhaps the most ingenious aspect of this work is that the authors use the fact that their system must necessarily lose photons, which is usually an obstacle and annoyance, to access new topological physics,” says Mikael Rechtsman, an assistant professor of physics at Pennsylvania State University who was not involved in this work. “Without the loss … this would have required highly complex 3-D fabrication methods that likely would not have been possible.” In other words, he says, the technique they developed “gave them access to 2-D physics that would have been conventionally thought impossible.”

    The work was supported by the Army Research Office through the Institute for Soldier Nanotechnologies; S3TEC, an Energy Frontier Research Center funded by the U.S. Department of Energy; the U.S. Air Force; and the National Science Foundation.

    See the full article here .

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  • richardmitnick 12:28 pm on January 7, 2018 Permalink | Reply
    Tags: Andrea Adamo and Jennifer Baltz, , , , Drug manufacturing that’s out of this world, MIT, Zaiput Flow Technologies   

    From MIT: “Drug manufacturing that’s out of this world” 

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    January 5, 2018
    Rob Matheson

    1
    In the continuous-flow liquid-liquid separator developed by MIT spinout Zaiput Flow Technologies, liquid mix (blue and pink) is pumped through a feed tube to a porous polymer membrane (dotted line). One liquid (pink) is drawn to the surface of the membrane, while the other (blue) is repelled. An internal mechanical pressure controller maintains a slight pressure differential between the two sides of the membrane. This pushes the attracted liquid through the membrane without the repelled one, sending each liquid through separate tubes. Courtesy of Zaiput Flow Technologies.

    Continuous-flow chemistry device used for drug production could find use in long-duration space missions.

    Liquid-liquid separation and chemical extraction are key processes in drug manufacturing and many other industries, including oil and gas, fragrances, food, wastewater filtration, and biotechnology.

    Three years ago, MIT spinout Zaiput Flow Technologies launched a novel continuous-flow liquid-liquid separator that makes those processes faster, easier, and more efficient. Today, nine pharmaceutical giants and a growing number of academic labs and small companies use the separator.

    Having proved its efficacy on Earth, the separator is now being tested as a tool for manufacturing drugs and synthesizing chemicals in outer space.

    In 2015, Zaiput won a Galactic Grant from the Center for the Advancement of Science in Space that allows companies to test technologies on the International Space Station (ISS). On Dec. 15, after two years of development and preparation, Zaiput launched its separator in a SpaceX rocket as part of the CRS-13 cargo resupply mission that will last one month.

    As long-duration space travel and extraterrestrial habitation becomes a potential reality, it’s important to find ways to synthesize chemicals for drugs, food, fuels, and other products in space that may be important for those missions, says Zaiput co-founder and CEO Andrea Adamo SM ’03, who co-invented the separator in the lab of Klavs Jensen, the Warren K. Lewis Professor of Chemical Engineering. Notably, Zaiput’s separator, called SEP-10, separates liquids without the need for gravity, which is a trademark of traditional methods.

    “When people go on deep space explorations, or maybe to Mars, these are multiyear missions,” Adamo says. “But how do you synthesize chemicals for drugs and other products without gravity? We have that answer. Testing our unit in space will show that what we have done on Earth is fully exportable to space.”

    Results from the ISS experiments will prove that the device indeed functions in zero-gravity, which is basically impossible to verify on Earth. And, they will help the startup refine the device, Adamo says: “MIT strives for excellence and we inherited that model — we’re still striving for excellence.”

    Surface forces

    In traditional liquid-liquid separators, a mixture of two liquids of different densities is fed into a funnel-shaped settling tank. The heavier liquid sinks and can be drained out through a valve, away from the lighter liquid, which stays on top. But the separation process is time-consuming, and some chemicals can decay or become unstable while sitting in the tank.

    Instead of leveraging gravity, Zaiput’s separator uses surface forces to attract or repel a liquid from a membrane. As an example, consider a nonstick pan: Oil spreads on the pan, but water beads up because it has an affinity to bond with the polymer covering the pan, while oil does not.

    Zaiput’s separator uses the same principle. A mixture of liquids is pumped through a feed tube and travels to a porous polymer membrane. One liquid is drawn to the surface of the membrane, while the other is repelled. An internal mechanical pressure controller maintains a slight pressure differential between one side of the membrane and the other. This differential is just enough to push the attracted liquid through the porous membrane without pushing the repelled one. The attracted liquid then goes out through one tube, while allowing the repelled liquid to flow out through a separate tube. Flow rates range from 0 to 12 milliliters per minute.

    “If you want to use this for a continuous operation in a reliable way, you have to carefully control pressure conditions across membranes,” Adamo says. “You want a little bit of pressure, so the chemical goes through, but not too much to push through the unwanted liquid. The internal controller ensures this happens at all times.”

    Zaiput’s separator also improves chemical extraction, which is different from liquid separation. Imagine working with a mixture of wine and oil. Liquid separation means separating the mixture into individual flows, of wine and oil. Extraction, however, means removing the ethanol chemical from the wine, along with separating the liquids, which is of interest to chemists.

    For chemical extraction, a “feed” liquid that contains a target chemical for extraction and a “solvent” — which is incapable of mixing with the feed liquid — are combined in a tube that flows toward the separation device. The solvent captures the target chemical from the feed because the chemical is soluble in it; the separation devices then separate two streams, with the solvent containing the target chemical. In the wine-oil example, the ethanol would be removed by the oil solvent.

    Zaiput units can be equipped with different types of membranes to achieve specific effects, or connected in a series of units.

    Importantly, Adamo says, Zaiput’s continuous-flow, membrane-based separator allows for separation of emulsions, whereby small droplets of one liquid end up in the other liquid, never fully separating. “We don’t have that issue, because we don’t need to wait for liquids to settle,” Adamo says. “We are the only technology that provides continuous separation, can readily separate emulsions, and is also designed for safety, so if you’re dealing with explosive or toxic substances, you can process them quickly.”

    Beautifying and scaling up

    Adamo came to MIT in the early 2000s as a civil engineer. Conducting research at MIT and being exposed to the Institute’s entrepreneurial ecosystem, however, “changed my horizons,” he says. “I wanted to be in a field where I could bring technology to the world through a startup.”

    Civil engineering had some limits in that regard, so Adamo started experimenting in the fast-moving field of microfluidics, working as a researcher in the lab of Jensen, a pioneer of flow chemistry. Inspired by Jensen’s previous research into surface forces, Adamo began designing a small, membrane-based separation device equipped with a precise pressure controller that maintained exact conditions for separation. This first prototype consisted of two bulky plastic pieces bolted together. “It was really ugly,” Adamo says.

    But showcasing the prototype to colleagues at MIT, he found that despite its unaesthetic appearance, the device had commercial potential. “The innovation was not just good for the lab, but also for general public,” he says. “I started looking into business propositions.” (So far, the research has also produced two papers co-authored by Jensen, Adamo, and other MIT researchers in Industrial & Engineering Chemistry Research Membrane-Based, Liquid–Liquid Separator with Integrated Pressure Control and Design of Multistage Counter-Current Liquid–Liquid Extraction for Small-Scale Applications.)

    In 2013, Adamo co-founded Zaiput with partner and Harvard University biochemist Jennifer Baltz, now Zaiput’s chief operating officer, with help from MIT’s Venture Mentoring Service and other MIT services.

    The startup designed a far more appealing product. Growing up in Italy, Adamo says, he was always surrounded by beautiful, colorful scenery and objects. He used that background as inspiration for the separator’s design, turning the prototype into a series of handheld, colorful blocks. Lab units are orange; larger units are purple, gold, or lime green. There is also color coding for different devices that are made of different materials.

    “Customers visit labs and these devices pop out,” Adamo says. “Function is key, but when you take an object in your hands, it has to feel nice. It has to be pleasing to the eye and, in a commercial sense, distinctive.”

    Currently, Zaiput is developing a production-scale device with a flow rate of 3,000 milliliters per minute, for larger-scale drug manufacturing. The startup is also hoping to more efficiently tackle very complex chemical extractions. Today, this involves repeating chemical extraction processes multiple times in massive columns, about 100 feet high, to ensure as much of the target chemical has been extracted from a liquid. But Zaiput hopes it can do the same with a small system of combined modular units. Additionally, the startup hopes to bring the device to traditional batch-separation users, notably those who still work with settling tanks.

    “The next challenges are bigger-scale development, more complex extraction, and reaching out to traditional users to empower them with new technologies,” Adamo says.

    See the full article here .

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  • richardmitnick 2:14 pm on December 30, 2017 Permalink | Reply
    Tags: a new algorithm termed state-space multitaper time-frequency analysis (SS-MT), Electroencephalograms, Medical Engineering and Computational Neuroscience, MIT, MIT researchers analyzed raw brain activity data, , Recalculating time, Spectrogram estimation is a standard analytic technique applied commonly in a number of problems, State-space modeling is a flexible paradigm which has been broadly applied to analyze data whose characteristics evolve over time   

    From MIT: “Recalculating time” 

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    December 21, 2017
    Sara Cody | Brain and Cognitive Sciences

    1
    Using a novel analytical method they have developed, MIT researchers analyzed raw brain activity data (B). The spectrogram shows decreased noise and increased frequency resolution, or contrast (E and F) compared to standard spectral analysis methods (C and D). Image courtesy of Seong-Eun Kim et al.

    Whether it’s tracking brain activity in the operating room, seismic vibrations during an earthquake, or biodiversity in a single ecosystem over a million years, measuring the frequency of an occurrence over a period of time is a fundamental data analysis task that yields critical insight in many scientific fields. But when it comes to analyzing these time series data, researchers are limited to looking at pieces of the data at a time to assemble the big picture, instead of being able to look at the big picture all at once.

    In a new study, MIT researchers have developed a novel approach to analyzing time series data sets using a new algorithm, termed state-space multitaper time-frequency analysis (SS-MT). SS-MT provides a framework to analyze time series data in real-time, enabling researchers to work in a more informed way with large sets of data that are nonstationary, i.e. when their characteristics evolve over time. It allows researchers to not only quantify the shifting properties of data but also make formal statistical comparisons between arbitrary segments of the data.

    “The algorithm functions similarly to the way a GPS calculates your route when driving. If you stray away from your predicted route, the GPS triggers the recalculation to incorporate the new information,” says Emery Brown, the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience, a member of the Picower Institute for Learning and Memory, associate director of the Institute for Medical Engineering and Science, and senior author on the study.

    “This allows you to use what you have already computed to get a more accurate estimate of what you’re about to compute in the next time period,” Brown says. “Current approaches to analyses of long, nonstationary time series ignore what you have already calculated in the previous interval leading to an enormous information loss.”

    In the study, Brown and his colleagues combined the strengths of two existing statistical analysis paradigms: state-space modeling and multitaper methods. State-space modeling is a flexible paradigm, which has been broadly applied to analyze data whose characteristics evolve over time. Examples include GPS, tracking learning, and performing speech recognition. Multitaper methods are optimal for computing spectra on a finite interval. When combined, the two methods bring together the local optimality properties of the multitaper approach with the ability to combine information across intervals with the state-space framework to produce an analysis paradigm that provides increased frequency resolution, increased noise reduction and formal statistical inference.

    To test the SS-MT algorithm, Brown and colleagues first analyzed electroencephalogram (EEG) recordings measuring brain activity from patients receiving general anesthesia for surgery. The SS-MT algorithm provided a highly denoised spectrogram characterizing the changes in power across frequencies over time. In a second example, they used the SS-MT’s inference paradigm to compare different levels of unconsciousness in terms of the differences in the spectral properties of these behavioral states.

    “The SS-MT analysis produces cleaner, sharper spectrograms,” says Brown. “The more background noise we can remove from a spectrogram, the easier it is to carry out formal statistical analyses.”

    Going forward, Brown and his team will use this method to investigate in detail the nature of the brain’s dynamics under general anesthesia. He further notes that the algorithm could find broad use in other applications of time-series analyses.

    “Spectrogram estimation is a standard analytic technique applied commonly in a number of problems such as analyzing solar variations, seismic activity, stock market activity, neuronal dynamics and many other types of time series,” says Brown. “As use of sensor and recording technologies becomes more prevalent, we will need better, more efficient ways to process data in real time. Therefore, we anticipate that the SS-MT algorithm could find many new areas of application.”

    Seong-Eun Kim, Michael K. Behr, and Demba E. Ba are lead authors of the paper, which was published online the week of Dec. 18 in Proceedings of the National Academy of Sciences PLUS. This work was partially supported by a National Research Foundation of Korea Grant, Guggenheim Fellowships in Applied Mathematics, the National Institutes of Health including NIH Transformative Research Awards, funds from Massachusetts General Hospital, and funds from the Picower Institute for Learning and Memory.

    See the full article here .

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  • richardmitnick 2:10 pm on December 24, 2017 Permalink | Reply
    Tags: , Dongkeun Park: Winding his way to medical insights, , FBML-Francis Bitter Magnet Laboratory, High-field superconducting magnets are vital for nuclear magnetic resonance (NMR) spectroscopy, MIT, MIT’s Plasma Science and Fusion Center, NIH-National Institutes of Health, Nuclear magnetic resolution spectroscopy, , Research Engineer Dongkeun Park, The stronger the NMR magnet the greater the detail and resolution in imaging the molecular structure of proteins providing researchers with the information they may need to develop medications for com   

    From MIT: “Dongkeun Park: Winding his way to medical insights” 

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    December 22, 2017
    Paul Rivenberg | Plasma Science and Fusion Center

    Francis Bitter Magnet Lab researcher continues a decades-long pursuit to create a revolutionary magnet for nuclear magnetic resolution spectroscopy.

    1
    Research Engineer Dongkeun Park (right) and his colleague Juan Bascuñán wind a double-pancake coil with high-temperature superconductor. Photo: Paul Rivenberg/PSFC

    2
    Assisted by postdoc Jiho Lee, Dongkeun Park inspects the wiring of a completed HTS coil in preparation for testing it in liquid helium. Photo: Paul Rivenberg/PSFC

    3
    In the completed 1.3 GHz magnet, the three HTS coils (pink) that make up the H800 magnet are nested within the LTS coils composing the L500 (blue). Image courtesy of PSFC

    4
    Research Engineer Phil Michael transfers liquid helium to the cryostat in preparation for testing the middle of the three HTS coils as Dongkeun Park looks on. Park and his colleagues expect to test the three-coil assembled H800 magnet in early in 2018. Photo: Paul Rivenberg/PSFC

    Research engineer Dongkeun Park watches a thin, coppery tape of high-temperature superconductor (HTS) wind its way from one spool on his plywood worktable to another, cautiously overseeing the speed and tension of the tape’s journey.

    When completed, in about half a day, this HTS double-pancake (DP) winding will look like two flat coils, one atop the other, but they will be one, connected internally, leaving both terminal ends on the outside. Park has been managing this process on and off for eight years, knowing that every turn of the coil creates a stronger magnet. This is just one of 96 double pancake coils that have been wound over the past five years for an 800 MHz HTS insert coil, the H800, being built in the Francis Bitter Magnet Laboratory (FBML) at MIT’s Plasma Science and Fusion Center.

    High-field superconducting magnets are vital for nuclear magnetic resonance (NMR) spectroscopy, a technology that provides a unique insight into biological processes. The stronger the NMR magnet, the greater the detail and resolution in imaging the molecular structure of proteins, providing researchers with the information they may need to develop medications for combating disease.

    Park joined the laboratory as a postdoc in 2009. He traces his interest in superconductivity, and MIT, to a lecture given by visiting FBML magnetic technology division head Yuki Iwasa at Yongsei University in Seoul, South Korea. Park says that as a graduate student in electrical engineering, “I wanted to make something by hand, not only by calculation.”

    When Park first arrived at FBML, the lab had been working on high-resolution HTS-based NMR magnets since 1999 as part of a program sponsored by the National Institutes of Health (NIH) to complete a 1-GHz NMR magnet with a combination of low temperature superconductor (LTS) and HTS double-pancake insert coils. The lab’s work on LTS-based NMR began several decades earlier.

    At the time of his arrival, NIH and MIT had recently agreed to increase the target strength of the magnet being developed from 1 GHz to 1.3 GHz. To reach this strength, FBML planned to create an H600 magnet and nest it inside a 700 MHz LTS (L700) magnet, which could be purchased elsewhere. Park notes that this combination translates to a magnetic field strength of 30.5 Tesla, “which would make it the world’s strongest magnet for NMR applications.”

    One responsibility given to Park, along with his colleague research engineer Juan Bascuñán, was to wind each DP, then test it in liquid nitrogen. The DPs would then be stacked, compressed, joined together and retested as a finished coil. Finally, this stacked coil would be over-banded with layers of stainless steel tape to support the much larger electromagnetic forces generated during high-current operation in liquid helium. Park and his colleagues needed to create two of these coils, one slightly larger than the other, and nest them inside a series of LTS coils to create the final magnet. The combined coils would create a magnet that could provide the sharpest imaging yet for investigating protein structure, possibly three times the image resolution from FBML’s current 900-MHz NMR.

    In December 2011, Park and his colleagues had virtually finished the preliminary DP windings, and were looking forward to stacking them for further testing. But returning from MIT’s winter recess, they discovered that the coils were missing. The 112 double pancake coils they had carefully crafted and wound for the H600 had been stolen.

    Park’s current PSFC colleague, research scientist Phil Michael, suggests that the theft, though traumatic to the project, “ultimately made the magnet better.” To save money, MIT and NIH decided that instead of purchasing an L700 magnet to surround the H600 coils as originally planned, they could use an L500 coil already on hand at FBML, and create for it a higher strength HTS magnet: the H800.

    With new security measures in place, Iwasa’s group set out to accomplish this goal by adopting a new HTS magnet technology known as no-insulation winding, developed by Park along with former FBML research engineer Seungyong Hahn. All previous coils had been created from HTS tape insulated with plastic film or high resistive metal. The new coils would be made without the insulation, allowing them to become more compact and mechanically robust, with increased current density.

    Park did not take part in the early production of the H800. In February of 2012, he decided to pursue an opportunity to make a new commercial magnetic resonance imaging (MRI) magnet for Samsung Electronics in South Korea and the UK. In 2016 he happily returned to MIT as a research engineer, his hiatus having provided him an appreciation for the benefits of an academic environment.

    “A company’s objective is to make a profit. So you must always be concerned with reducing costs,” he says. “This is very different from exploring basic science and engineering on innovative ideas at MIT.”

    Although many coils for the H800 had been wound in his absence, he returned in time to complete and test more than half the required DP coils, along with team members Bascuñán, Phil Michael, Jiho Lee, Yoonhyuck Choi, and Yi Li. As 2018 approaches the three HTS coils necessary to create the H800 are nearly completed. Only Coil 3 remains to be finally tested in liquid helium. As the new year begins, the coils will be combined and tested as the H800.

    But even after the H800 is nested in the L500 coils and the target 1.3 GHz magnet is created, there will still be three to four years of work to ready it for the high-resolution NMR spectroscopy that will provide new insights into biological structures. Until then, Park will remain patient as he looks to other projects he is overseeing, including one developing an MRI magnet for screening osteoporosis.

    And yes, his new project requires superconducting coils. Park is always ready to start winding.

    See the full article here .

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  • richardmitnick 1:54 pm on December 23, 2017 Permalink | Reply
    Tags: Creating underwater robots that can go places humans simply cannot, For this artificial intelligence to be effective in the water students need to combine software skills with ocean engineering expertise, In underwater marine robotics there is a unique need for artificial intelligence — it’s crucial, MIT, Students put their AI software for underwater vehicles to the test on the Charles River, Unlocking marine mysteries with artificial intelligence, We are trying to clone the oceanographer and put our understanding of how the ocean works into the robot   

    From MIT: “Unlocking marine mysteries with artificial intelligence” 

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    December 14, 2017
    Mary Beth O’Leary | Department of Mechanical Engineering

    1
    Class 2.680 (Unmanned Marine Vehicle Autonomy, Sensing and Communications), which is offered during spring semester, is structured around the presence of ice on the Charles. While the river is covered by a thick sheet of ice in February and into March, students are taught to code and program a remotely-piloted marine vehicle for a given mission. Image: Teresa Lin.

    2
    “They’re not working with a toy,” says Schmidt’s co-instructor, Research Scientist Michael Benjamin. “We feel it’s important that they learn how to extend the software — write their own sensor processing models and AI behavior. And then we set them loose on the Charles.” Image: John Freidah.

    Students put their AI software for underwater vehicles to the test on the Charles River.

    Each year the melting of the Charles River serves as a harbinger for warmer weather. Shortly thereafter is the return of budding trees, longer days, and flip-flops. For students of class 2.680 (Unmanned Marine Vehicle Autonomy, Sensing and Communications), the newly thawed river means it’s time to put months of hard work into practice.

    Aquatic environments like the Charles present challenges for robots because of the severely limited communication capabilities. “In underwater marine robotics, there is a unique need for artificial intelligence — it’s crucial,” says MIT Professor Henrik Schmidt, the course’s co-instructor. “And that is what we focus on in this class.”

    The class, which is offered during spring semester, is structured around the presence of ice on the Charles. While the river is covered by a thick sheet of ice in February and into March, students are taught to code and program a remotely-piloted marine vehicle for a given mission. Students program with MOOS-IvP, an autonomy software used widely for industry and naval applications.

    “They’re not working with a toy,” says Schmidt’s co-instructor, Research Scientist Michael Benjamin. “We feel it’s important that they learn how to extend the software — write their own sensor processing models and AI behavior. And then we set them loose on the Charles.”

    As the students learn basic programming and software skills, they also develop a deeper understanding of ocean engineering. “The way I look at it, we are trying to clone the oceanographer and put our understanding of how the ocean works into the robot,” Schmidt adds. This means students learn the specifics of ocean environments — studying topics like oceanography or underwater acoustics.

    Students develop code for several missions they will conduct on the Charles River by the end of the semester. These missions include finding hazardous objects in the water, receiving simulated temperature and acoustic data along the river, and communicating with other vehicles.

    “We learned a lot about the applications of these robots and some of the challenges that are faced in developing for ocean environments,” says Alicia Cabrera-Mino ’17, who took the course last spring.

    Augmenting robotic marine vehicles with artificial intelligence is useful in a number of fields. It can help researchers gather data on temperature changes in our ocean, inform strategies to reverse global warming, traverse the 95 percent of our oceans that has yet to be explored, map seabeds, and further our understanding of oceanography.

    According to graduate student Gregory Nannig, a former navigator in the U.S. Navy, adding AI capabilities to marine vehicles could also help avoid navigational accidents. “I think that it can really enable better decision making,” Nannig explains. “Just like the advent of radar or going from celestial navigation to GPS, we’ll now have artificial intelligence systems that can monitor things humans can’t.”

    Students in 2.680 use their newly acquired coding skills to build such systems. Come spring, armed with the software they’ve spent months working on and a better understanding of ocean environments, they enter the MIT Sailing Pavilion prepared to test their artificial intelligence coding skills on the recently melted Charles River.

    As marine vehicles glide along the Charles, executing missions based on the coding students have spent the better part of a semester perfecting, the mood is often one of exhilaration. “I’ve had students have big emotions when they see a bit of AI that they’ve created,” Benjamin recalls. “I’ve seen people call their parents from the dock.”

    For this artificial intelligence to be effective in the water, students need to combine software skills with ocean engineering expertise. Schmidt and Benjamin have structured 2.680 to ensure students have a working knowledge of these twin pillars of robotic marine vehicle autonomy.

    By combining these two research areas in their own research, Schmidt and Benjamin hope to create underwater robots that can go places humans simply cannot. “There are a lot of applications for better understanding and exploring our ocean if we can do it smartly with robots,” Benjamin adds.

    See the full article here .

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  • richardmitnick 1:35 pm on December 23, 2017 Permalink | Reply
    Tags: , ATM-Auto-Tuned Models, Auto-tuning data science: New research streamlines machine learning, , Empowering data scientists, MIT,   

    From MIT: “Auto-tuning data science: New research streamlines machine learning” 

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    December 19, 2017
    MIT Laboratory for Information and Decision Systems

    1
    To solve complex problems, data scientists must shepherd their raw data through a series of steps, each one requiring many human-driven decisions. The last step in the process, deciding on a modeling technique, is particularly crucial. No image credit.

    A new automated machine-learning system performs as well or better than its human counterparts — and works 100 times faster.

    The tremendous recent growth of data science — both as a discipline and an application — can be attributed, in part, to its robust problem-solving power: It can predict when credit card transactions are fraudulent, help business owners figure out when to send coupons in order to maximize customer response, or facilitate educational interventions by forecasting when a student is on the cusp of dropping out.

    To get to these data-driven solutions, though, data scientists must shepherd their raw data through a complex series of steps, each one requiring many human-driven decisions. The last step in the process, deciding on a modeling technique, is particularly crucial. There are hundreds of techniques to choose from — from neural networks to support vector machines — and selecting the best one can mean millions of dollars of additional revenue, or the difference between spotting a flaw in critical medical devices and missing it.

    In a paper called ATM: A distributed, collaborative, scalable system for automated machine learning [https://cyphe.rs/static/atm.pdf], which was presented last week at the IEEE International Conference on Big Data, researchers from MIT and Michigan State University present a new system that automates the model selection step, even improving on human performance. The system, called Auto-Tuned Models (ATM), takes advantage of cloud-based computing to perform a high-throughput search over modeling options, and find the best possible modeling technique for a particular problem. It also tunes the model’s hyperparameters — a way of optimizing the algorithm — which can have a substantial effect on performance. ATM is now available for enterprise as an open-source platform.

    To compare ATM with human performers, the researchers tested the system against users of a collaborative crowdsourcing platform, openml.org. On this platform, data scientists work together to solve problems, finding the best solution by building on each other’s work. ATM analyzed 47 datasets from the platform and was able to deliver a solution better than the one humans had come up with 30 percent of the time. When it couldn’t outperform humans, it came very close, and crucially, it worked much more quickly than humans could. While open-ml users take an average of 100 days to deliver a near-optimal solution, ATM can arrive at an answer in less than a day.

    Empowering data scientists

    This level of speed and accuracy offers much-needed peace of mind for data scientists, who are often plagued by “what-ifs.” “There are so many options,” says Arun Ross, professor in the computer science and engineering department at Michigan State University and a senior author on the paper. “If a data scientist chose support vector machines as a modeling technique, the question of whether a neural network or a different model would have resulted in better accuracy always lingers in her mind.”

    Over the past few years, the problem of model selection/tuning has become the focus of a whole new subfield of machine learning, known as Auto-ML. Auto-ML solutions aim to provide data scientists with the best possible model for a given machine-learning task. There’s just one problem: Competing Auto-ML approaches yield different results, and their methods are often opaque. In other words, while seeking to solve one selection problem, the community created another that is even more complex. “The ‘what-if’ question still remains,” says Kalyan Veeramachaneni, a principal research scientist at MIT’s Laboratory for Information and Decision Systems (LIDS) and a senior author on the paper. “It simply shifts to, ‘what if we used a different Auto-ML approach?’”

    The ATM system works differently, using on-demand cloud computing to generate and compare hundreds (or even thousands) of models overnight. To search through techniques, researchers use an intelligent selection mechanism. The system tests thousands of models in parallel, evaluates each, and allocates more computational resources to those techniques that show promise. Poor solutions fall by the wayside, while the best options rise to the top.

    Rather than blindly choosing the “best” one and providing it to the user, ATM displays results as a distribution, allowing for comparison of different methods side-by-side. In this way, Ross says, ATM speeds up the process of testing and comparing different modeling approaches without automating out human intuition, which remains a vital part of the data science process.

    Open-source, community-driven approach

    By streamlining the process of model choice, Veeramachaneni and his team aim to allow data scientists to work on more impactful parts of the pipeline. “We hope that our system will free up experts to spend more time on understanding the data, problem formulation, and feature engineering,” Veeramachaneni says.

    To that end, the researchers are open-sourcing ATM, making it available to enterprises who might want to use it. They have also included provisions that allow researchers to integrate new model selection techniques and thus continually improve on the platform. ATM can run on a single machine, local computing clusters, or on-demand clusters in the cloud, and can work with multiple data sets and multiple users simultaneously.

    “A small- to medium-sized data science team can set up and start producing models with just a few steps,” Veeramachaneni says. And none of those are followed by a “what-if.”

    See the full article here .

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  • richardmitnick 8:27 am on December 16, 2017 Permalink | Reply
    Tags: , Engineers create plants that glow, , MIT, Nanobionic light-emitting plants, , The mixture of nanoparticles was infused into the leaf using lab-designed syringe termination adaptors   

    From MIT: “Engineers create plants that glow” 

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    December 12, 2017
    Anne Trafton

    1
    Illumination of a book (“Paradise Lost,” by John Milton) with the nanobionic light-emitting plants (two 3.5-week-old watercress plants). The book and the light-emitting watercress plants were placed in front of a reflective paper to increase the influence from the light emitting plants to the book pages. Image: Seon-Yeong Kwak

    2
    Glowing MIT logo printed on the leaf of an arugula plant. The mixture of nanoparticles was infused into the leaf using lab-designed syringe termination adaptors. The image is merged of the bright-field image and light emission in the dark. Image: Seon-Yeong Kwak

    Illumination from nanobionic plants might one day replace some electrical lighting.

    Imagine that instead of switching on a lamp when it gets dark, you could read by the light of a glowing plant on your desk.

    MIT engineers have taken a critical first step toward making that vision a reality. By embedding specialized nanoparticles into the leaves of a watercress plant, they induced the plants to give off dim light for nearly four hours. They believe that, with further optimization, such plants will one day be bright enough to illuminate a workspace.

    “The vision is to make a plant that will function as a desk lamp — a lamp that you don’t have to plug in. The light is ultimately powered by the energy metabolism of the plant itself,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT and the senior author of the study.

    This technology could also be used to provide low-intensity indoor lighting, or to transform trees into self-powered streetlights, the researchers say.

    MIT postdoc Seon-Yeong Kwak is the lead author of the study, which appears in the journal Nano Letters.


    Video: Melanie Gonick/MIT

    Nanobionic plants

    Plant nanobionics, a new research area pioneered by Strano’s lab, aims to give plants novel features by embedding them with different types of nanoparticles. The group’s goal is to engineer plants to take over many of the functions now performed by electrical devices. The researchers have previously designed plants that can detect explosives and communicate that information to a smartphone, as well as plants that can monitor drought conditions.

    Lighting, which accounts for about 20 percent of worldwide energy consumption, seemed like a logical next target. “Plants can self-repair, they have their own energy, and they are already adapted to the outdoor environment,” Strano says. “We think this is an idea whose time has come. It’s a perfect problem for plant nanobionics.”

    To create their glowing plants, the MIT team turned to luciferase, the enzyme that gives fireflies their glow. Luciferase acts on a molecule called luciferin, causing it to emit light. Another molecule called co-enzyme A helps the process along by removing a reaction byproduct that can inhibit luciferase activity.

    The MIT team packaged each of these three components into a different type of nanoparticle carrier. The nanoparticles, which are all made of materials that the U.S. Food and Drug Administration classifies as “generally regarded as safe,” help each component get to the right part of the plant. They also prevent the components from reaching concentrations that could be toxic to the plants.

    The researchers used silica nanoparticles about 10 nanometers in diameter to carry luciferase, and they used slightly larger particles of the polymers PLGA and chitosan to carry luciferin and coenzyme A, respectively. To get the particles into plant leaves, the researchers first suspended the particles in a solution. Plants were immersed in the solution and then exposed to high pressure, allowing the particles to enter the leaves through tiny pores called stomata.

    Particles releasing luciferin and coenzyme A were designed to accumulate in the extracellular space of the mesophyll, an inner layer of the leaf, while the smaller particles carrying luciferase enter the cells that make up the mesophyll. The PLGA particles gradually release luciferin, which then enters the plant cells, where luciferase performs the chemical reaction that makes luciferin glow.

    The researchers’ early efforts at the start of the project yielded plants that could glow for about 45 minutes, which they have since improved to 3.5 hours. The light generated by one 10-centimeter watercress seedling is currently about one-thousandth of the amount needed to read by, but the researchers believe they can boost the light emitted, as well as the duration of light, by further optimizing the concentration and release rates of the components.

    Plant transformation

    Previous efforts to create light-emitting plants have relied on genetically engineering plants to express the gene for luciferase, but this is a laborious process that yields extremely dim light. Those studies were performed on tobacco plants and Arabidopsis thaliana, which are commonly used for plant genetic studies. However, the method developed by Strano’s lab could be used on any type of plant. So far, they have demonstrated it with arugula, kale, and spinach, in addition to watercress.

    For future versions of this technology, the researchers hope to develop a way to paint or spray the nanoparticles onto plant leaves, which could make it possible to transform trees and other large plants into light sources.

    “Our target is to perform one treatment when the plant is a seedling or a mature plant, and have it last for the lifetime of the plant,” Strano says. “Our work very seriously opens up the doorway to streetlamps that are nothing but treated trees, and to indirect lighting around homes.”

    The researchers have also demonstrated that they can turn the light off by adding nanoparticles carrying a luciferase inhibitor. This could enable them to eventually create plants that shut off their light emission in response to environmental conditions such as sunlight, the researchers say.

    The research was funded by the U.S. Department of Energy.

    See the full article here .

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  • richardmitnick 4:36 pm on December 11, 2017 Permalink | Reply
    Tags: , MIT, , , Researchers Find Simpler Way to Deposit Magnetic Iron Oxide onto Gold Nanorods   

    From NC State and MIT: “Researchers Find Simpler Way to Deposit Magnetic Iron Oxide onto Gold Nanorods” 

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    December 11, 2017
    Joe Tracy, NC State
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    1
    Mixing silica-overcoated gold nanorods (left) and iron oxide nanoparticles (center) yields iron oxide-overcoated gold nanorods (right). Credit: Brian Chapman.

    Researchers from North Carolina State University and MIT have found a simpler way to deposit magnetic iron oxide (magnetite) nanoparticles onto silica-coated gold nanorods, creating multifunctional nanoparticles with useful magnetic and optical properties.

    Gold nanorods have widespread potential applications because they have a surface plasmon resonance – meaning they can absorb and scatter light. And by controlling the dimensions of the nanorods, specifically their aspect ratio (or length divided by diameter), the wavelength of the absorbed light can be controlled. This characteristic makes gold nanorods attractive for use in catalysis, security materials and a host of biomedical applications, such as diagnostics, imaging, and cancer therapy. The fact that the magnetite-gold nanoparticles can also be manipulated using a magnetic field enhances their potential usefulness for biomedical applications, such as diagnostic tools or photothermal therapeutics.

    “The approach we outline in our new paper is simple, likely making it faster and less expensive than current techniques for creating these nanoparticles – on a small scale or a large one,” says Joe Tracy, an associate professor of materials science and engineering at NC State and corresponding author of a paper on the work.

    The new technique uses an approach called heteroaggregation. Silica-coated gold nanorods are dispersed in ethanol, a polar solvent. In ethanol, the hydrogen atoms are partially positively charged, and the oxygen atoms are partially negatively charged. The magnetite nanoparticles are dispersed in hexanes, a non-polar solvent, where the charges are not separated. When the two solutions are mixed, the magnetite nanoparticles bind to the gold nanorods – and the resulting magnetite-gold nanoparticles are removed from the solvent using a simple centrifugation process.

    “We are able to take pre-synthesized, silica-coated gold nanorods and iron oxide nanoparticles and then combine them,” says Brian Chapman, a Ph.D. student at NC State and lead author of the paper. “This is simpler than other techniques, which rely on either growing iron oxide nanoparticles on gold nanorods or using molecular cross-linkers to bind the iron to the silica coating of the nanorods.”

    “Our approach also results in highly uniform nanoparticles,” Tracy says. “And by incorporating ligands called PEG-catechols, the resulting nanoparticles can be dispersed in water. This makes them more useful for biomedical applications.

    “These are interesting, and potentially very useful, multifunctional nanoparticles,” Tracy adds. “And hopefully this work will facilitate the development of applications that capitalize on them.”

    The paper, Heteroaggregation Approach for Depositing Magnetite Nanoparticles onto Silica-Overcoated Gold Nanorods, is published in the journal Chemistry of Materials. The paper was co-authored by Wei-Chen Wu, a former Ph.D. student at NC State; and Qiaochu Li and Niels Holten-Andersen of MIT. The work was done with support from the National Science Foundation under grants DMR-1121107, DMR-1056653, and CBET-1605699.

    See the full article here .

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    NC State students, faculty and staff take problems in hand and work with industry, government and nonprofit partners to solve them. Our 34,000-plus high-performing students apply what they learn in the real world by conducting research, working in internships and co-ops, and performing acts of world-changing service. That experiential education ensures they leave here ready to lead the workforce, confident in the knowledge that NC State consistently rates as one of the best values in higher education.

     
  • richardmitnick 3:45 pm on December 7, 2017 Permalink | Reply
    Tags: , C3E 2017 Clean Energy Symposium, , , MIT,   

    From MIT: “A bipartisan message of clean energy progress” 

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    December 7, 2017
    Francesca McCaffrey

    1
    MIT Vice President for Research Maria Zuber and former U.S. Secretary of Energy Ernest Moniz, the Cecil and Ida Green Professor of Physics and Engineering Systems emeritus at MIT, engaged in a fireside chat at the C3E Women in Clean Energy Symposium, discussing technology, policy, and the importance of women’s leadership in STEM fields. Photo: Justin Knight

    In the face of global challenges, leading women in energy and climate convene at the C3E 2017 Clean Energy Symposium.

    The diverse group of energy leaders who spoke at the 2017 Clean Energy, Education, and Empowerment (C3E) Women in Clean Energy Symposium hailed from different professional, personal, and political backgrounds, bringing many viewpoints on the conference’s theme of transforming energy infrastructure — nationally and internationally — for a transition to a low-carbon future. Though opinions on the best strategies to bring about this transition differed, all agreed on the urgency of deploying strategies and technologies to achieve it.

    “It’s inspiring to be surrounded by so many women at different stages of their careers, approaching clean energy issues from a wide range of perspectives and professions,” MIT Energy Initiative (MITEI) executive director Martha Broad told the audience, which included industry professionals, government officials, and academic researchers, as well as students who were giving poster presentations.

    3

    “MITEI is thrilled to host this event, celebrate our awardees, and hear from thought leaders in this space.” Broad is also a U.S. C3E ambassador — part of a cohort of senior leaders in business, government, and academia who serve as role models and advocates for women in clean energy.

    Now in its sixth year being held at MIT, the C3E Symposium brings women at all stages of their careers together to discuss solutions to the most pressing energy issues of the day and to celebrate awardees from various disciplines. Founded under the auspices of the 25-government Clean Energy Ministerial, the U.S. C3E Initiative aims to advance clean energy by helping to close the gender gap and enabling the full participation of women in the clean energy sector. MITEI and the U.S. Department of Energy (DOE) have collaborated on the symposium since 2012, and the Stanford Precourt Institute for Energy joined the collaboration in 2016.

    Inclusive clean energy solutions for the future

    Panels throughout the two-day conference focused on strategies across the technology, policy, and business spheres to address energy challenges both local and global. Nevada State Senator Pat Spearman stressed the importance of forward-looking governance on a panel about innovative policies. For Spearman, innovation means taking advantage of Nevada’s natural energy resources, from an abundance of solar energy in the south to the potential for geothermal in the north. It also means developing progressive policies that facilitate timely regulatory changes in response to new and emerging technologies.

    Spearman is particularly determined to account for low-income constituents with provisions in energy policy measures.

    “We need to always include the fact that those who are on the lower spectrum of the income level are usually the ones who are the least likely to adopt because the price has not come down far enough,” she said. ”So those who can afford it do, and those who can’t, don’t. For me, it’s a matter of environmental and economic justice.”

    On a panel about the future of the electric grid, Marcy Reed, National Grid’s chief of business operations, expanded on the importance of being mindful of customers’ needs.

    “We have 20th-century infrastructure operating in a world with 21st-century demands,” she said, adding that at Massachusetts-based National Grid, and her colleagues take their cue on how to best affect change from their customers. “They’re savvy and passionate and environmentally-minded. They also want their energy delivery system to be modern and responsive to their needs.” She added that having the right tools and information enables customers to make energy-efficient choices.

    Ugwem Eneyo, a Stanford University graduate and co-founder of Solstice Energy Solutions, explained how data are similarly important to her customers in sub-Saharan Africa.

    “With the development and integration of solar and storage into the energy mix, data and connectivity will play a significant role in enabling future distributed energy grids, and will also play a significant role in driving efficiency and productivity of these distributed energy assets,” Eneyo said. Her company’s technology uses a data-driven approach to intelligently manage distributed energy, helping consumers plan for their own cost- and energy-efficient power use.

    As a panelist for a session on international energy infrastructure developments, Radhika Khosla discussed ongoing changes in India’s energy system.

    “Not only is India a very large emitter, but it is also one of the most vulnerable countries to climate change,” said Khosla, who is a visiting scientist at the MIT Tata Center for Technology and Design. Citing rising temperatures, impending infrastructure and demographic transitions, and increased air pollution as a few among several factors, Khosla added, “What happens to India in terms of its growth trajectory matters not only in the global context, but also in the Indian context.”

    Leveraging women’s expertise for the clean energy transition

    Underscoring the bipartisan message of the importance of women’s involvement in the clean energy transition, U.S. Secretary of Energy Rick Perry gave a video keynote address in which he noted the positive effect that gatherings like the C3E Symposium can have in trying to address current energy challenges.

    “Each of you here today helps advance innovation, connect new ideas with existing markets, and use technology to promote clean energy solutions,” Perry said. “But even more importantly, your work will inspire the next generation of women leaders in STEM, and that is sorely needed.”

    Secretary Perry’s predecessor under President Obama, Ernest Moniz, engaged in a fireside chat with MIT Vice President for Research Maria T. Zuber, the E. A. Griswold Professor of Geophysics. Zuber and Moniz, who is the Cecil and Ida Green Professor of Physics and Engineering Systems Emeritus and special advisor to the MIT president, discussed the need for a rapid transition to a low-carbon economy and also highlighted the significance of initiatives like C3E in the mission to support and increase women’s involvement in STEM fields.

    “If you can see it, you can be it”

    Every year, C3E honors mid-career women who have made particular contributions to their area of energy and invites previous awardees to attend the conference. This year’s award-winners were: Anna Bautista, vice president of construction and workforce development for Grid Alternatives (Advocacy Award); Leslie Marshall, corporate energy engineering lead for General Mills (Business Award); Nicole Lautze, associate faculty member at the University of Hawaii Manoa and founder of the Hawaii Groundwater and Geothermal Resources Center (Education Award); Emily Kirsch, founder and CEO of intelligent energy incubator Powerhouse (Entrepreneurship Award); Chris LaFleur, program lead for Hydrogen Safety, Codes, and Standards at Sandia National Laboratories (Government Award); Allison Archambault, president of EarthSpark International (International Award); Sarah Valdovinos, co-founder of Walden Green Energy (Law and Finance Award); and Inês M.L. Azevedo, principal investigator and co-director for the Climate and Energy Decision-Making Center at Carnegie Mellon University (Research Award).

    Senators Lisa Murkowski (R-Alaska) and Maria Cantwell (D-Washington) were co-recipients of the C3E Lifetime Achievement award for their work on energy issues, including their leadership roles on the Senate Energy and Natural Resources Committee and their stewardship of the bipartisan Energy and Natural Resources Act of 2017.

    In her prerecorded remarks, Murkowski said “We all recognize [that] women bring a different perspective to problem-solving, so it’s imperative, whether in your fields or mine, if we want to find the best and most innovative solutions to our biggest challenges, the female perspective must be present and active at the decision table.”

    Cantwell, in written remarks delivered by C3E Ambassador Melanie Kenderdine, said, “I am proud to work alongside you as we continue to celebrate the women who are making incredible achievements in clean energy.”

    Carol Battershell, principal deputy director of the DOE’s Office of Energy Policy and Systems Analysis and a U.S. C3E ambassador, noted how meaningful it was for the C3E ambassadors to have the honor of choosing the awardees. Several other speakers also remarked on how it felt to be in the presence of a group of such impactful leaders and diverse practitioners in the clean energy sector.

    Sherina Maye Edwards, energy commissioner for the Illinois Commerce Commission, prefaced her comments by saying, “So often, I am on the road talking to rooms full of people who look nothing like me. It is so nice to see not just such a fantastic group of women, but also such a diverse group of women.”

    Awardee Emily Kirsch, who attended the first C3E conference in 2013, met many C3E ambassadors there who mentored and encouraged her while she was launching her company. Accepting the Entrepreneurship Award, Kirsch said, “C3E is a testament to the idea that if you can see it, you can be it.”

    See the full article here .

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  • richardmitnick 2:21 pm on December 2, 2017 Permalink | Reply
    Tags: , , , , , MIT, , Plasmas, Study sheds light on turbulence in astrophysical plasmas, Turbulent state of solar wind   

    From MIT: “Study sheds light on turbulence in astrophysical plasmas” 

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    December 1, 2017
    David L. Chandler

    1
    Magnetic reconnection is a complicated phenomenon that Nuno Loureiro, an associate professor of nuclear science and engineering and of physics at MIT, has been studying in detail for more than a decade. To explain the process, he gives a well-studied example: “If you watch a video of a solar flare” as it arches outward and then collapses back onto the sun’s surface, “that’s magnetic reconnection in action. It’s something that happens on the surface of the sun that leads to explosive releases of energy.” Loureiro’s understanding of this process of magnetic reconnection has provided the basis for the new analysis that can now explain some aspects of turbulence in plasmas. Image: NASA

    Theoretical analysis uncovers new mechanisms in plasma turbulence.

    Plasmas, gas-like collections of ions and electrons, make up an estimated 99 percent of the visible matter in the universe, including the sun, the stars, and the gaseous medium that permeates the space in between. Most of these plasmas, including the solar wind that constantly flows out from the sun and sweeps through the solar system, exist in a turbulent state. How this turbulence works remains a mystery; it’s one of the most dynamic research areas in plasma physics.

    Now, two researchers have proposed a new model to explain these dynamic turbulent processes.

    The findings, by Nuno Loureiro, an associate professor of nuclear science and engineering and of physics at MIT, and Stanislav Boldyrev, a professor of physics at the University of Wisconsin at Madison, are reported today in The Astrophysical Journal. The paper is the third in a series this year explaining key aspects of how these turbulent collections of charged particles behave.

    “Naturally occurring plasmas in space and astrophysical environments are threaded by magnetic fields and exist in a turbulent state,” Loureiro says. “That is, their structure is highly disordered at all scales: If you zoom in to look more and more closely at the wisps and eddies that make up these materials, you’ll see similar signs of disordered structure at every size level.” And while turbulence is a common and widely studied phenomenon that occurs in all kinds of fluids, the turbulence that happens in plasmas is more difficult to predict because of the added factors of electrical currents and magnetic fields.

    “Magnetized plasma turbulence is fascinatingly complex and remarkably challenging,” he says.

    2
    Simulation conducted by MIT student Daniel Groselj.

    Loureiro and Boldyrev found that magnetic reconnection must play a crucial role in the dynamics of plasma turbulence, an insight that they say fundamentally changes the understanding of the dynamics and properties of space and astrophysical plasmas and “is indeed a conceptual shift in how one thinks about turbulence,” Loureiro says.

    Existing hypotheses about the dynamics of plasma turbulence “can correctly predict some aspects of what is observed,” he says, but they “lead to inconsistencies.”

    Loureiro worked with Boldyrev, a leading theorist on plasma turbulence, and the two realized “we can fix this by essentially merging the existing theoretical descriptions of turbulence and magnetic reconnection,” Loureiro explains. As a result, “the picture of turbulence gets conceptually modified and leads to results that more closely match what has been observed by satellites that monitor the solar wind, and many numerical simulations.”

    Loureiro hastens to add that these results do not prove that the model is correct, but show that it is consistent with existing data. “Further research is definitely needed,” Loureiro says. “The theory makes specific, testable predictions, but these are difficult to check with current simulations and observations.”

    He adds, “The theory is quite universal, which increases the possibilities for direct tests.” For example, there is some hope that a new NASA mission, the Parker Solar Probe, which is planned for launch next year and will be observing the sun’s corona (the hot ring of plasma around the sun that is only visible from Earth during a total eclipse), could provide the needed evidence. That probe, Loureiro says, will be going closer to the sun than any previous spacecraft, and it should provide the most accurate data on turbulence in the corona so far.

    Collecting this information is well worth the effort, Loureiro says: “Turbulence plays a critical role in a variety of astrophysical phenomena,” including the flows of matter in the core of planets and stars that generate magnetic fields via a dynamo effect, the transport of material in accretion disks around massive central objects such as black holes, the heating of stellar coronae and winds (the gases constantly blown away from the surfaces of stars), and the generation of structures in the interstellar medium that fills the vast spaces between the stars. “A solid understanding of how turbulence works in a plasma is key to solving these longstanding problems,” he says.

    “This important study represents a significant step forward toward a deeper physical understanding of magnetized plasma turbulence,” says Dmitri Uzdensky, an associate professor of physics at the University of Colorado, who was not involved in this work. “By elucidating deep connections and interactions between two ubiquitous and fundamental plasma processes — magnetohydrodynamic turbulence and magnetic reconnection — this analysis changes our theoretical picture of how the energy of turbulent plasma motions cascades from large down to small scales.”

    He adds, “This work builds on a previous pioneering study published by these authors earlier this year and extends it into a broader realm of collisionless plasmas. This makes the resulting theory directly applicable to more realistic plasma environments found in nature. At the same time, this paper leads to new tantalizing questions about plasma turbulence and reconnection and thus opens new directions of research, hence stimulating future research efforts in space physics and plasma astrophysics.”

    The research was supported by a CAREER award from the National Science Foundation and the U.S. Department of Energy through the Partnership in Basic Plasma Science and Engineering.

    See the full article here .

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